Outstanding Student AwardIn recognition of significant contributions to the IEOR Department, this award goes to students who have represented the department with grace and intelligence.

3. Semester:Personal Leadership & SuccessPersonal Leadership and Success takes the view that to succeed professionally one needs to develop another dimension of leadership consisting of the ability to understand and direct one's internal environment–goals, motivations, mindsets, and emotions.Until recently, the only way to explore this mastery of the inner environment has been through the teachings of philosophers, prophets, or self-help "gurus." These historical and modern sources of wisdom essentially rely on faith while Personal Leadership and Success replaces this approach with scientifically validated, practical insights and techniques for understanding and mastering one's inner environment.

Business Analytics for ORBusiness analytics refers to the ways in which enterprises such as businesses, non-profits, and governments can use data to gain insights and make better decisions. Business analytics is applied in operations, marketing, finance, and strategic planning among other functions. The ability to use data effectively to drive rapid, precise and profitable decisions has been a critical strategic advantage for companies as diverse as WalMart, Google, Capital One, and Disney. In this course, you will learn how to identify, evaluate, and capture business analytic opportunities that create value. Toward this end, you will learn basic analytic methods and analyze case studies on organizations that successfully deployed these techniques. In the first part of the course, we focus on how to use data to develop insights and predictive capabilities using machine learning, data mining and forecasting techniques. In the second part, we focus on the use of optimization to support decision-making in the presence of a large number of alternatives and business constraints. Finally, throughout the course, we explore the challenges that can arise in implementing analytical approaches within an organization.

Managerial NegotiationThere are two purposes for this course: to develop your ability to negotiate in a purposeful, principled and effective way; and to teach you how to manage complex conflicts and deals, and lead groups to wise agreements. The course relies heavily on simulated negotiations in and out of class. We'll also use lectures, case studies, exercises, games, videos, and demonstrations. As we advance in the course, our focus will shift from simple one-on-one negotiations to more complex ones involving many parties, agents, coalitions, and organizations. The cases and simulations we'll use along the way will cover a wide range of business situations, including a troubled software partnership, a business acquisition, a key partnership decision and a group-on-group re-negotiation of an international aircraft engine deal.

Service OperationsThis course examines both traditional and new approaches for achieving operational competitiveness in service businesses. Major service sectors such as health care, repair / technical support services, banking and financial services, transportation, restaurants, hotels and resorts are examined. The course addresses strategic analysis and operational decision making, with emphasis on the latter. Its content also reflects results of a joint research project with the consulting firm Booz Allen Hamilton, which was initiated in 1996 to investigate next-generation service operations strategy and practices. Topics include the service concept and operations strategy, the design of effective service delivery systems, productivity and quality management, response time (queueing) analysis, capacity planning, yield management and the impact of information technology. This seminar is intended for students interested in consulting, entrepreneurship, venture capital or general management careers that will involve significant analysis of a service firm’s operations.

2. Semester:Stochastic ModelsThis course introduces students to operations research and stochastic processes. Operations research is concerned with quantitative decision problems, generally involving the allocation and control of limited resources, often in the presence of significant uncertainty. Stochastic processes are collections of random variables, usually indexed by time. [In stochastic process models, time can be regarded as either discrete or continuous.] For example, we might use stochastic processes to model the evolution of a stock price over time, the damage claims received by an insurance company over time, the work-in-process inventory in a factory over time or the number of calls waiting in a telephone call center over time, all of which evolve with considerable uncertainty. Among the stochastic processes to be considered are discrete-time Markov chains, random walks, continuous-time Markov chains, Poisson processes, birth-and-death processes, renewal processes, renewal-reward processes, Brownian motion and geometric Brownian motion. Among the engineering applications to be considered are queuing, inventory and finance.

Supply Chain ManagementSupply chain management entails managing the flow of goods and information through a production or distribution network to ensure that the right goods are delivered to the right place in the right quantity at the right time. Two primary objectives are to gain competitive edge via superior customer service and to reduce costs through efficient procurement, production and delivery systems. Supply chain management encompasses a wide range of activities — from strategic activities, such as capacity expansion or consolidation, make/buy decisions and initiation of supplier contracts, to tactical activities, such as production, procurement and logistics planning, to, finally, operational activities, such as operations scheduling and release decisions, batch sizing and issuing of purchase orders.

Game-Theoretic Business StrategyThe course has three objectives.1) Provide you with the theory to understand why a given company is (or is not) profitable. (For potential entrepreneurs, this theory becomes a tool to assess whether your proposed venture will be profitable in a competitive environment.)2) Provide you with perspectives for assessing the sustainability of a given company’s profitability. We will place special emphasis on understanding and evaluating the key assumptions and judgments underpinning your assessments.3) Enable you to identify the substantive issues behind the trends and frameworks in the strategy field.To achieve these objectives, the course will utilize case discussions, exercises, and lectures. One of the key challenges of strategy is that decisions have to be made with limited and ambiguous information. Cases will provide us with a great way to simulate the ‘messiness’ of real-world decisions. Additionally, and concurrently, the course will provide an introduction to recent work in game theory providing formal foundations for the economics of strategy. This will require both exercises and lectures.

Decision Models and ApplicationsStudents are introduced to deterministic and stochastic decision tools used by leading corporations and applied researchers, and apply these software packages to complex, real-world problems in engineering and finance. Building on a basic theoretical understanding of optimization, simulation and game theory obtained in prerequisite classes, students master commercial decision modeling programs such as Premium Solver Professional (linear, integer and non-linear optimization), TreePlan (decision-trees), Crystal Ball (simulation), and OptQuest (optimization under uncertainty). Students are also welcome to complete most modeling assignments with Matlab. After students have mastered the course software, its limitations and the frameworks for applying it, they work in small teams to address (as a mid-term project) one large-scale deterministic project and (as an end-of-semester project) one similarly-complex stochastic problem. While addressing their first projects, students learn effective presentation and project reporting skills, suitable for communicating with CFOs and CEOs. Students present their project analyses to a small panel of industry experts and executives. Throughout the course, the importance of outside-the-model considerations, model limitations and sources of modeling error are stressed, and general frameworks for approaching particular problem types are developed.

1. Semester:Deterministic ModelsThis class is an introduction to the fundamental methods used in deterministic operations research. Topics covered will include linear programming, network flows, dynamic programming, and nonlinear programming. While we shall discuss the underlying theory with some occasional proofs, the emphasis will be on modeling. Applications of these ideas in various settings will be discussed. Students will learn modeling skills, and develop the ability to build, analyze, and reason logically with models. They will also learn to design and analyze algorithms, and to distinguish good algorithms from not-so good ones. They will also appreciate the capabilities and limitations of deterministic models in operations research.

Operations ConsultingThis course aims to develop and harness the modeling, analytical and managerial skills of engineering students and apply them to improve the operations of both service and manufacturing firms. The course is structured as a hands-on laboratory in which students "learn by doing" on real-world consulting projects (October to May). The student teams focus on identifying, modeling and testing (and sometimes implementing) operational improvements and innovations with high potential to enhance the profitability and/or achieve sustainable competitive advantage for their sponsor companies. The course is targeted toward students planning careers in technical consulting (including operations consulting) and management consulting, or pursuing positions as business analysts in operations, logistics, supply chain and revenue management functions, positions in general management and future entrepreneurs.

Corporate FinanceIt is introductory only in the sense that we start with the assumption that some, if not most, students have never had any corporate finance courses previously. Otherwise, it is quite ambitious. At the end of it, you will know how to value a company. On the way the topics we shall cover include those that are important to all managers whether or not they specialize in finance: (1) procedures for analyzing companies’ financial data to determine how efficiently they have been run; (2) methods for projecting funding needs based on principles of good working capital management; (3) rules for choosing the maximal safe, or optimal, level of debt in the structure of capital used for funding company operations; (4) figuring the costs of the various types of funds that a company uses and its weighted average cost of capital; and (5) combining all the foregoing into a methodology, to wit, discounting free cash flows and adding the present value of the residual or salvage value, for establishing a company’s value or price.

Probability ModelsImagine yourself as an Amazon department manager who needs to decide how to stock up products at various distribution centers, subject to uncertain demands. Or imagine yourself as a Goldman Sachs trader who needs to decide how to trade commodities, subject to uctuating commodity prices. You have access to historical data, from which you may make certain predictions about the future, but you also know that the future is full of uncertainty. How can you make scientically sound decisions in these situations? This course is about making sense of data and uncertainty. We will learn how to understand data, visualize data, come up with sound statistical models of data, and reason probabilistically about these models.